Post edit processes are typically performed after machine translation of a document, and are often cumbersome processes. It will be understood that post editing processes may vary, depending upon the type of machine translation utilized to translate the document. Some machine translation processes involve the use of translation memory managers, often referred to as translation memory. These translation memory managers estimate the accuracy of machine translations by comparing the machine translations to translations stored in a database.
To create computer assisted translation (CAT) output, a document may be fragmented into segments, and memory translation and/or machine translation may be performed on each of the segments. It will be understood that segments may include either phrases or individual words. Next, one or more algorithms (e.g., linguistic rules, statistical knowledge, and so forth) may be applied to the segments. Additionally, by comparing the machine translated segments to previously translated segments, an estimate of the post editing complexity of the segment may be determined. For example, exact matches include translated segments that directly correspond (100% correspondence) to previously translated segments. For translated segments that do not directly match previously translated segments, confidence algorithms may be applied to the translated segments to determine a relative accuracy of the translation.
Moreover, while direct estimations of post editing complexity without the use of fuzzy matching algorithms are less expensive, post edit review of these directly estimated machine translations may require post editing analysis on each segment of the document.